Hierarchical drift diffusion modeling uncovers multisensory benefit in numerosity discrimination tasks

Abstract

Studies of accuracy and reaction time in decision making often observe a speed-accuracy tradeoff, where either accuracy or reaction time is sacrificed for the other. While this effect may mask certain multisensory benefits in performance when accuracy and reaction time are separately measured, drift diffusion models (DDMs) are able to consider both simultaneously. However, drift diffusion models are often limited by large sample size requirements for reliable parameter estimation. One solution to this restriction is the use of hierarchical Bayesian estimation for DDM parameters. Here, we utilize hierarchical drift diffusion models (HDDMs) to reveal a multisensory advantage in auditory-visual numerosity discrimination tasks. By fitting this model with a modestly sized dataset, we also demonstrate that large sample sizes are not necessary for reliable parameter estimation.

Cross-modal interactions at the audiovisual cocktail-party revealed by behavior, ERPs, and neural oscillations

“…Participants were able to identify and localize the target numeral most rapidly, when congruent audiovisual speech was present. Consistently, congruent audiovisual speech resulted in higher drift rates, indicating that the complementary visual information did in fact aid the evidence accumulation process, and suggesting that drift rate presents a sensitive and reliable measure of multisensory benefits (Chau et al, 2021; Murray et al, 2020). Overall, the behavioral results are consistent with the well-established audiovisual facilitation effect, demonstrating that bimodal stimulus presentation facilitates recognition accuracy, speeds up response times (Molholm et al 2004, Giard & Peronnet, 1999, Miller, 1982), and improves perceptual sensitivity (Wahn et al 2017).…”